Giulio Bottegal

CoRR, 2022

2021

Learning linear modules in a dynamic network using regularized kernel-based methods.

[BibT_eX]

[DOI]

Autom., 2021

2020

Identification of Linear Models From Quantized Data: A Midpoint-Projection Approach.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2020

2019

Boosting as a kernel-based method.

[BibT_eX]

[DOI]

Aleksandr Y. Aravkin

Mach. Learn., 2019

Modeling and identification of uncertain-input systems.

[BibT_eX]

[DOI]

Autom., 2019

Bayesian topology identification of linear dynamic networks.

[BibT_eX]

[DOI]

Shengling Shi

Proceedings of the 17th European Control Conference, 2019

Local module identification in dynamic networks with correlated noise: the full input case.

[BibT_eX]

[DOI]

Arne G. Dankers

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

An empirical Bayes approach to identification of modules in dynamic networks.

[BibT_eX]

[DOI]

Niklas Everitt

Autom., 2018

The generalized cross validation filter.

[BibT_eX]

[DOI]

Autom., 2018

A two-experiment approach to Wiener system identification.

[BibT_eX]

[DOI]

Ricardo Castro-Garcia

Johan A. K. Suykens

Autom., 2018

Local Module Identification in Dynamic Networks Using Regularized Kernel-Based Methods.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Preserving Privacy of Finite Impulse Response Systems.

[BibT_eX]

[DOI]

Farhad Farokhi

Iman Shames

IEEE Control. Syst. Lett., 2017

A nonparametric kernel-based approach to Hammerstein system identification.

[BibT_eX]

[DOI]

Autom., 2017

Variance analysis of linear SIMO models with spatially correlated noise.

[BibT_eX]

[DOI]

Autom., 2017

A new kernel-based approach to system identification with quantized output data.

[BibT_eX]

[DOI]

Autom., 2017

Probabilistic matrix factorization from quantized measurements.

[BibT_eX]

[DOI]

Johan A. K. Suykens

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Application-oriented input design for room occupancy estimation algorithms.

[BibT_eX]

[DOI]

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

On the identification of Wiener systems with polynomial nonlinearity.

[BibT_eX]

[DOI]

Ricardo Castro-Garcia

Johan A. K. Suykens

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

On the Zero-Freeness of Tall Multirate Linear Systems.

[BibT_eX]

[DOI]

Mohsen Zamani

Brian D. O. Anderson

IEEE Trans. Autom. Control., 2016

Robust EM kernel-based methods for linear system identification.

[BibT_eX]

[DOI]

Autom., 2016

Kernel-based system identification from noisy and incomplete input-output data.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Identification of modules in dynamic networks: An empirical Bayes approach.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015

Regularized Deconvolution-Based Approaches for Estimating Room Occupancies.

[BibT_eX]

[DOI]

IEEE Trans Autom. Sci. Eng., 2015

Modeling Complex Systems by Generalized Factor Analysis.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2015

A benchmark for data-based office modeling: challenges related to CO$_2$ dynamics.

[BibT_eX]

[DOI]

Marco Molinari

CoRR, 2015

A new kernel-based approach for overparameterized Hammerstein system identification.

[BibT_eX]

[DOI]

CoRR, 2015

Bayesian kernel-based system identification with quantized output data.

[BibT_eX]

[DOI]

CoRR, 2015

Blind identification strategies for room occupancy estimation.

[BibT_eX]

[DOI]

Proceedings of the 14th European Control Conference, 2015

On the estimation of initial conditions in kernel-based system identification.

[BibT_eX]

[DOI]

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

A new kernel-based approach to overparameterized Hammerstein system identification.

[BibT_eX]

[DOI]

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

On the variance analysis of identified linear MIMO models.

[BibT_eX]

[DOI]

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Multi-room occupancy estimation through adaptive gray-box models.

[BibT_eX]

[DOI]

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Outlier robust kernel-based system identification using ℓ1-Laplace techniques.

[BibT_eX]

[DOI]

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014

A kernel-based approach to Hammerstein system identification.

[BibT_eX]

[DOI]

CoRR, 2014

Blind system identification using kernel-based methods.

[BibT_eX]

[DOI]

CoRR, 2014

On the variance of identified SIMO systems with spatially correlated output noise.

[BibT_eX]

[DOI]

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013

Flocking and Generalized Factor Analysis

[BibT_eX]

[DOI]

CoRR, 2013

Regularized spectrum estimation using stable spline kernels.

[BibT_eX]

[DOI]

Autom., 2013

Estimation of building occupancy levels through environmental signals deconvolution.

[BibT_eX]

[DOI]

Proceedings of the BuildSys 2013, 2013

Modeling random flocks through Generalized Factor Analysis.

[BibT_eX]

[DOI]

Proceedings of the 12th European Control Conference, 2013

On the properties of linear multirate systems with coprime output rates.

[BibT_eX]

[DOI]

Mohsen Zamani

Brian D. O. Anderson

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012

Regularized spectrum estimation in spaces induced by stable spline kernels.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2012

2011

On the identifiability of errors-in-variables models with white measurement errors.

[BibT_eX]

[DOI]

Stefano Pinzoni

Autom., 2011

A note on generalized factor analysis models.

[BibT_eX]

[DOI]